CN103155331A - Method and device for producing a state signal - Google Patents

Abstract

The invention relates to a method for producing a state signal (Sz) that indicates a state of an energy transmission system, whereby, for pre-determined network nodes of the energy transmission system, electrical measuring values for at least one electrical measuring variable are measured and used to produce the state signal indicating the state. According to the invention, respectively predicted load data that predict the electrical behaviour of the respective load are associated with the electrical loads connected to the energy transmission system; the electrical loads are respectively associated with an electrical load group into which the electrical loads are collected with comparable prognosis reliability; an individual weighting value that describes the prognosis reliability of the predicted load data of the loads associated with the load group is respectively allocated to each load group; and the state signal is formed using the measuring values, the load data and the weighting values.

Description

Method and apparatus for generation of status signal

Technical field

The present invention relates to a kind of method for generation of status signal, this status signal has shown the state of energy transmission equipment, wherein measures about the electrical measured value of at least one electrical measurement parameter and produce the status signal of show state under the condition of introducing measured value for the predetermined network node of energy transmission equipment.Status signal for example may be displayed on current value, magnitude of voltage or the performance number in the network node of energy transmission equipment one, the measurement parameter of therefrom deriving, load estimation, power stream or indirectly or be directly involved in any other parameter of energy transmission equipment as " state ".As status signal, for example can produce the alarm signal of display alarm state, or show wrong rub-out signal.

Background technology

Usually arrange measuring transducer on all important network nodes in high-voltage fence, in order at any time can both determine reliably each state of high-voltage fence and for example take suitable measure in vicious situation.With it differently, the measuring transducer that usually lacks respective numbers in medium voltage network.Usually not that each network node that exists in electrical network has corresponding transducer, applied which voltage and phase angle on this network node thereby can not be informed in.

Summary of the invention

Therefore, the technical problem to be solved in the present invention is, a kind of method is provided, even in the time can not presenting the measured value of abundant actual measurement owing to lacking measuring transducer, and also can be fast and produce reliably status signal by the method.

According to the present invention, above-mentioned technical problem solves by the method that has according to the feature of claim 1.Preferred enforcement according to method of the present invention provides in the dependent claims.

Then according to the present invention, give the electric loading the be connected to energy transmission equipment load data of the prediction of the electrical characteristics of each load of distribution forecast respectively, electric loading is distributed to respectively the electric loading group, combine the electric loading with similar predicting reliability in described load group, distribute independent weighted value for respectively each load group, this independent weighted value has been described the predicting reliability of load data of the prediction of the load of distributing to load group, and forms status signal under the condition of the weighted value of introducing measured value, load data and load group.

Major advantage according to method of the present invention is, execution relatively rapidly that it can (for example utilize electronic data-processing equipment).Namely according to the present invention, with the load marshalling of considering in method, and form the load group that its load has respectively similar predicting reliability.Load group for example can consist of by industrial load: industrial load shows load characteristic extremely reliably usually, because this load characteristic is determined by operational process.Other load group for example can be passed through normal customer constitute, usually can not predict reliably its consumption characteristics as industrial property.By load being included into load group and considering the independent weighted value of load group, compare with the independent weighted value of working load and can realize that substantial speed improves.

Preferably, provide at least one that has respectively at least one energy consumption measurement device consume measured value electric loading load group and for the other load group that does not have the electric loading that consumes measured value.In the situation that electric loading is assigned to load group, preferably also consider to consume the existence of measured value except predicting reliability.

Be considered as equally preferably, measure at least one current weather measured value (Klimamesswert) and proofread and correct weighted value and/or load data under the condition of the weather measured value of introducing current measurement.If for example the weather measured value of current measurement is different from predetermined weather rated value, proofread and correct.

For the network node of energy transmission equipment for example also can Calculation Simulation measured parameter value, and can check the state of energy transmission equipment under the condition of the measured parameter value of introducing emulation.For example for the network node that does not have electrical measured value can Calculation Simulation measured parameter value.In other words, also can carry out " emulation " under the condition of the load data of introducing electrical measured value, prediction and weighted value in the scope of the method for moving energy transmission equipment.

According to another kind of method distortion, measured parameter value for the predetermined network node Calculation Simulation that has electrical measured value, the measured parameter value of this emulation is compared with the measured value of measurement, and the load data of form optimizing, method are to change the load data of prediction until minimum or reach or lower than predetermined threshold value in the measured parameter value of emulation and the deviation between electrical measured value.

At this, can consider to distribute to the weighted value of each load group when changing load data, method is that its weighted value has been shown that the load data of less predicting reliability has shown that than its weighted value the load data of larger predicting reliability changes in the larger context.

The invention still further relates to a kind of device for generation of status signal, this status signal has shown the state of energy transmission equipment.According to the present invention, this device has the interface for the input electrical measured value, and described electrical measured value is measured at least one electrical measurement parameter for the predetermined network node of energy transmission equipment; Has control device, it is applicable to: form load group, load is distributed to load group and distributed respectively independent weighted value to load group, this independent weighted value has been described the predicting reliability to the load data of the prediction of the load of load group distribution, and check the state of energy transmission equipment under the condition of introducing measured value, load data and weighted value, and produce the status signal of show state.

Description of drawings

The present invention is further illustrated below in conjunction with embodiment; In accompanying drawing:

Fig. 1 shows the embodiment of the energy transmission equipment with a plurality of measurement fragments,

Fig. 2 shows in detail the fragment according to the energy transmission equipment of Fig. 1,

Fig. 3 shows the various combination of the complex power that is calculated by electric current and voltage measuring value,

Fig. 4 shows another embodiment of the energy transmission equipment with a plurality of predetermined measurement fragments,

Fig. 5 show redefine measure fragment after according to the embodiment of Fig. 4,

Fig. 6 shows for the flow chart of explaining according to the embodiment of method of the present invention, and

Fig. 7 shows for another embodiment that carries out according to the device of method of the present invention.

For clarity sake use all the time identical Reference numeral for same or similar element in the accompanying drawings.

Embodiment

Typically adopt radially or tree-like feed-in structure in the energy transmission equipment of medium voltage network, for example with the form as the loop (Schleife) of open loop operation.Only provide electrical measurement in the feed-in position in this energy transmission equipment, but usually not at each network node place of energy transmission equipment.In other words, only the network node of a small amount of energy transform device has electrical measurement.Electrical measurement is for example curtage measuring equipment or the power-measuring device that can measure active power and/or reactive power.Therefore not that form with current electrical measured value presents usually about the information of the load that is connected to energy transmission equipment, but only present with the form of the load data of the prediction of value acquisition rule of thumb.The load data of prediction for example can be with about the form of the normalized load curve of active-power P or reactive power Q or with about active-power P and power factor

The form of normalized load curve present.

Fig. 1 illustrates the energy transmission equipment as the open loop operation.Energy transmission equipment has a plurality of electrical measuring devices, measures fragment MA1 to MA8 and defines by them; Each measures fragment take measuring equipment as the boundary at this.Come mark measuring equipment and the arrow by downward orientation to come the mark load by intersection in Fig. 1.

Because do not have measuring equipment in measuring fragment, so if determine quantitatively to be applied to electrical measurement parameter on this network node, must implement emulation for the network node that is positioned at wherein.

Preferably, consider inter alia for such emulation, numerically mate at the measurement parameter of the interface of measurement fragment adjacent one another are.Especially, avoided power deviation at the interface of measurement fragment adjacent one another are.A rear condition is difficult to satisfy, because usually only provide current measuring device at many network nodes places and be not to present information about active power and reactive power for each network node thus.

Fig. 2 illustrates adjacent measurement fragment and how to flow coupled to each other by power: measure by one another measurement fragment of power stream inflow that fragment flows out.The optimization that this fact can be incorporated into the load characteristic of the load that connects is estimated.The coupling of adjacent measurement fragment can be incorporated into iterative computation thus, the load flow that implement to be used for total energy transmission equipment in this iterative computation is calculated and estimates, by these estimation matched load data and avoided the difference power of the interface between adjacent measurement fragment.

Treat in an identical manner herein load data and electrical measured value and (if present) pseudo-measured value in the method for estimation of exemplary description.Consider the different quality of information by different weighted values.For example by having guaranteed for the high weighting of the measured value of real actual measurement in other words or high weighted value, it is in the situation that emulation and optimization " are encountered (getroffen) " does not change by emulation and optimization in other words.By can guarantee for the low weighting of the load data of pseudo-measured value and prediction or low weighted value, it is in the situation that emulation can be changed in relative large scope with optimization and emulation and/or optimized algorithm can be restrained with calculating.By using the weighted sum weighted value also can accurately process incongruent load, method is to distribute less weighted value than the load that meets.

In the embodiment that here explains, for the estimated service life load data as state variable.After having implemented the calculation of power flowmeter, directly introduce voltage and current.The structured data that described estimation neither needs to measure fragment does not need its electricity to lead yet.The load that described estimation is only need to be in different iterative steps measured and, at loss and the load of the boundary of measuring fragment.Obviously reduced expense in the situation that carry out method of estimation in each iterative step in this way.

Realize in the situation that carry out further obviously reducing in each measurement fragment, load being grouped into load group of method of estimation computing cost.Load group can form or comprise described load by having identical information quality (predicting reliability) and its load characteristic with the load that similar reliability or accuracy are predicted.Correspondingly, in the situation that the load of identical load group is considered in estimation and emulation by identical weighted value.

For the measurement fragment with one whole group of active power (P) and reactive power (Q) measurement mechanism, estimation procedure is quite simple.Determine in the following way load, namely its corresponding to measure at each power segment boundaries place's feed-in and that measure and.Only loss needs to be considered in the iterative process of back.

Calculating in following measurement fragment is more difficult, and the measurement segment boundaries of described measurement fragment is only constructed has a current measuring device.Namely current measurement value can not be directly used in determining of load information.Figure 3 illustrates, the annular region that is used for complex power has only been described in current measurement.That is, must be further processed current value.

For example measure fragment for each and implement individually further processing about the current value of P and the pseudo-measured value of Q.Measure for having each that measure segment boundaries place current measurement value minimizing that fragment can be implemented as follows:

（1） $\underset{i}{\overset{\mathrm{NLG}}{\mathrm{\Σ}}}(w_i^{P,\mathrm{LG}}{\left(P_i^{\mathrm{LG}}(k_i^P-1)\right)}^2+w_i^{Q,\mathrm{LG}}{\left(Q_i^{\mathrm{LG}}(k_i^Q-1)\right)}^2)\→\min$

Wherein introduce following condition:

（2） ${(\underset{i=1}{\overset{\mathrm{NLG}}{\mathrm{\&Sigma;}}}{k}_i^P{P}_i^{\mathrm{LG}}+\mathrm{\&Delta;P})}^2+{(\underset{i=1}{\overset{\mathrm{NLG}}{\mathrm{\&Sigma;}}}{k}_i^Q{Q}_i^{\mathrm{LG}}+\mathrm{\&Delta;Q})}^2-V^2{I_{\mathrm{<figure-callout\; id="2"\; label="M"\; filenames="HDA00003041487000011.png"\; state="\{\{state\}\}">M</figure-callout>}}}^2=0$

Wherein:

NLG measures the quantity of the load group in fragment at each,

By active power and the reactive power of load curve or the load group (load master data) that measure to obtain by load data or by puppet,

Be used for the P of each load group and the weight coefficient of Q,

The measured value that is used for the estimation of the P of each load group and Q,

Δ P, Δ Q each measure loss in fragment and, or rather in loss and all inner losses that produces of measuring the segment boundaries place and measuring,

V is at the voltage of measuring the segment boundaries place, from last inner power flow solution

Middle acquisition, and

I _MAt the electric current of measuring segment boundaries place measurement.

Use the value of determining

With

As being used for that next time inner power flowmeter is calculated and the new load data of estimating step next time.

Preferably, the measurement fragment with the current measurement value that only need convert therein begins the conversion of current measurement value.

Usually express, preferred " from bottom to top " implemented to convert, wherein only to have a current measurement value and not calculated measurement fragment begins.Consider the feed-in position 2 in Fig. 1, namely consider measurement fragment 6 after measuring fragment 7 and 8, because this measurement fragment 6 has two network nodes with current measurement value.Namely at first convert and measure fragment 7 and 8.This process has reduced also not have the quantity of the current measurement value of conversion in measuring fragment 6.Reduce step by step the quantity of current measurement value, until all are all converted.

In the situation that following situation can occur for fenestral fabric or parallel feed-in: the current measurement value at not all measurement segment boundaries place measuring fragment can convert in the mode of describing.Can differently treat remaining current measurement value with following another kind of example explanation thus.

Preferably, measure fragment for each and implement individually electric current is scaled P and the pseudo-measured value of Q, and need not to consider to measure the coupling of fragment.Can consider coupling in the estimating step subsequently that gathers complete network.

Preferably, next step is forced, and is consistent at the stream at the measurement segment boundaries place of adjacent measurement fragment.

Estimation problem can be understood to minimizing of target J, and this target is described in equation (3).The first of equation (3) considers, the difference between the power information of the value of measuring and estimation is minimized; Second portion supervisor minimizing for the difference in load information.The third and fourth part is considered poor between the voltage and current of measuring and estimate.Additionally must satisfy following equal conditions:

-for effective active power of the estimation of true measurement and pseudo-measured value and the active power that is provided by true generator and, make up active power loss (equation (4)).

Effective reactive power Q of the estimation of-true measurement and pseudo-measured value and the reactive power that is provided by true generator and electric capacity and, make up reactive power loss (equation (5)).

-for each the measurement fragment with the pseudo-measured value that is calculated by current measurement value, the value of estimation

And V _cMust satisfy equation (3).

$J=\min \left(\underset{i=1}{\overset{\mathrm{NPQ}}{\mathrm{\&Sigma;}}}\right[w_i^{\mathrm{PW}}{(P_i^E-P_i^m)}^2+w_i^{\mathrm{QM}}{(Q_i^E-Q_i^m)}^2]$

$+\underset{i=1}{\overset{\mathrm{NLG}}{\mathrm{\&Sigma;}}}[w_i^{\mathrm{PLG}}{\left(P_i^{\mathrm{LG}}(k_i^P-1)\right)}^2+w_i^{\mathrm{QLG}}{\left(Q_i^{\mathrm{LG}}(K_i^Q-1)\right)}^2]$

（3） $+\underset{i=1}{\overset{\mathrm{NI}}{\mathrm{\&Sigma;}}}{w}_i^{\mathrm{IM}}{(I_i^E-I_i^m)}^2$

$+\underset{i=1}{\overset{\mathrm{NI}}{\mathrm{\&Sigma;}}}{w}_i^{\mathrm{VM}}{(V_i^E-V_i^m)}^2)$

Boundary condition wherein:

（4） $\underset{i=1}{\overset{\mathrm{NMK}}{\mathrm{\&Sigma;}}}{P}_i^E+\underset{i=1}{\overset{\mathrm{NGK}}{\mathrm{\&Sigma;}}}{P}_i^{\mathrm{Gen}}-\underset{i=1}{\overset{\mathrm{NLGK}}{\mathrm{\&Sigma;}}}{k}_i^P{P}_i^{\mathrm{LG}}-P_{\mathrm{loss}}^k=0$

（5） $\underset{i=1}{\overset{\mathrm{NMK}}{\mathrm{\&Sigma;}}}{Q}_i^E+\underset{i=1}{\overset{\mathrm{NGK}}{\mathrm{\&Sigma;}}}{Q}_i^{\mathrm{Gen}}+\underset{i=1}{\overset{\mathrm{NCK}}{\mathrm{\&Sigma;}}}{Q}_i^{\mathrm{Cap}}-\underset{i=1}{\overset{\mathrm{NLGK}}{\mathrm{\&Sigma;}}}{k}_i^Q{Q}_i^{\mathrm{LG}}-Q_{\mathrm{loss}}^k=0$

（6） ${\left(P_c^E\right)}^2+{\left(Q_c^E\right)}^2-{\left(V_c{I}_c^E\right)}^2=0$

Wherein

The sum of NPQ power measurement values in system comprises the power measurement values that is calculated by current measurement value,

The sum of NLG load group,

The quantity of the load group of NLGK in measuring fragment k,

The sum of NI current measurement value,

NMK P/Q measures right quantity, and it is calculated by the galvanometer in measuring fragment k,

The quantity of the generator of NGK in measuring fragment k,

The quantity of the electric capacity of NCK in measuring fragment k,

The weight coefficient that is used for active power value, reactive power value and current measurement value,

About active power and the reactive power of the estimation of measuring for the i time,

About the electric current of the estimation of measuring for the i time,

I measured electric current height,

Measured active power and reactive power comprise the pseudo-measured value of being derived by electric current,

The weighted value that is used for active power and reactive power for i load group,

In i load group for the proportionality coefficient of the estimation of power,

Active power and reactive power in i load group,

The active power of i generator and reactive power,

About the voltage of the estimation of measuring for the i time,

I measured voltage,

V _cThe voltage that is used for power conversion,

Power loss in measuring fragment k, and

Estimated result for the electric current that is scaled power.

Preferably, for electric current being scaled power and selecting following scheme for the estimation of holonomic system:

（7） J(x)=(x-x ^M) ^TW(x-x ^M)→min

Wherein:

x ^MThe vector of (true and pseudo-) metrical information,

The vector of the state variable that x estimates, and

The diagonal matrix of W weight coefficient.

This estimates the preferred boundary condition of considering all existence

（8） g _i(x)=0，

It is by stipulating for the equation (2) of the conversion of electric current and by equation (4), (5) and (6) for the estimation of whole system.Have in use under the condition of Lagrange's multiplier of the Lagrangian as described by following equation and can solve the optimization problem with equal boundary condition:

（9） $L(x,\mathrm{\&lambda;})=J\left(x\right)-\underset{i}{\overset{m}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_i{g}_i\left(x\right)=J\left(x\right)-{\mathrm{\&lambda;}}^{T}g\left(x\right)$

Wherein

λ is as the vector of Lagrange's multiplier.

Must satisfy following equation in this solution:

（10） $\&dtri;L(x,\mathrm{\&lambda;})=0$

（11） $\frac{\&PartialD;L}{\&PartialD;x}=0\&DoubleRightArrow;W(x_i^M-x_i)+G^T\mathrm{\&lambda;}=0$

（12） $\frac{\&PartialD;L}{\&PartialD;\mathrm{\&lambda;}}=0\&DoubleRightArrow;g\left(x\right)=0$

Under the condition of using newton Rui Pusenfa (Newton-Raphson-Methode), preferably solve iteratively the non-linear equation of this group:

（13） $\left[\begin{array}{cc}W& {\mathrm{<figure-callout\; id="0"\; label="G\; T\; G"\; filenames="HDA00003041487000071.png"\; state="\{\{state\}\}">G</figure-callout>}}^T& \\ G& 0\end{array}\right]\left[\begin{array}{c}\mathrm{\&Delta;x}\\ -\mathrm{\&lambda;}\end{array}\right]=\left[\begin{array}{c}\mathrm{W\&Delta;}{\hat{x}}^k\\ -g\left(x^k\right)\end{array}\right]$

Wherein:

x ^kThe solution of the k time iteration,

x ^MMeasure, comprise the pseudo-vector of measuring,

Δ x=x ^k+1-x ^kAbout the vector of the difference between the result of the iterative step of in succession following at two,

About measure and the k time iteration result between the vector of difference,

About the matrix of the partial derivative of condition vector, and

The vector of λ Lagrange's multiplier.

If there are two or more current measurement values in the place in the measurement segment boundaries, for example can like this current measurement value be scaled pseudo-power stream information, namely at first change all current measurement values, this causes having only another measurement fragment of a current measurement value of also not changing.In this way, also do not have the quantity of measurement electric current of conversion fewer and feweri.Radially with similar tree-like network in can use this process all the time.

Yet for the network with fenestral fabric or parallel feed-in, this process is not to reach target.Fig. 4 illustrates latticed topological structure.Measure in Fig. 4 fragment by Reference numeral MA represent, motor by G represent, electric capacity by C represent, the arrow of load group by downward orientation represents and measurement point represents by large stain.

Preferred and differently switching current I0 and the feed-in of I1(ring-type of top description in this arrangement) and I2 and the parallel feed-in of I3().For example in the situation that estimate impedance in direct consideration loop and the coupling of branch.Each branch of fragment with current information of a plurality of remnants can be defined as independent measurement fragment, and it has the meritorious and wattless power measurement value of definition in its each end.This measured value can be called virtual, because it is not to be derived by real current measurement value.

For the branch from network node i to j, can be according to the following complex power of determining in both sides:

$\left[\begin{array}{c}{\underset{\&OverBar;}{S}}_{\mathrm{ij}}\\ {\underset{\&OverBar;}{S}}_{\mathrm{ji}}\end{array}\right]=\left[\begin{array}{cc}{\underset{\&OverBar;}{V}}_i& 0\\ 0& {\underset{\&OverBar;}{V}}_j\end{array}\right]{\left[\begin{array}{c}{\underset{\&OverBar;}{I}}_i\\ {\underset{\&OverBar;}{I}}_j\end{array}\right]}^{*}=\left[\begin{array}{cc}{\underset{\&OverBar;}{V}}_i& 0\\ 0& {\underset{\&OverBar;}{V}}_j\end{array}\right]{\left(\begin{array}{c}\left[\begin{array}{cc}{\underset{\&OverBar;}{Y}}_{\mathrm{ii}}& {\underset{\&OverBar;}{Y}}_{\mathrm{ij}}\\ {\underset{\&OverBar;}{Y}}_{\mathrm{ji}}& {\underset{\&OverBar;}{Y}}_{\mathrm{jj}}\end{array}\right]\left[\begin{array}{c}{\underset{\&OverBar;}{V}}_i\\ {\underset{\&OverBar;}{V}}_j\end{array}\right]\end{array}\right)}^{*}$

Wherein

V _i, V _jComplex number voltage at node i and node j place,

S _nmComplex power from node n to node m, n wherein, m ∈ [i, j], and

Y _nmThe parameter of branch, n wherein, m ∈ [i, j],

Extract power information from previous load flow is calculated, and further use as the measured value with less weighted value (weight coefficient).

Preferably, only carry out the calculating of virtual power measurement values for this side of branch that is connected with node in grid network.If provide real power measurement values for branch's side, do not carry out this calculating.

Fig. 5 shows according to Fig. 4 has the measurement fragment of new formation and the network of corresponding virtual measured value.The measurement fragment that does not comprise the new formation of branch also can be called virtual node region.In Fig. 5, the measurement fragment that the original measurement fragment represents, newly forms with Reference numeral MA with Reference numeral NMA represent, generator by G represent, electric capacity by C represent, load group by the arrow of downward orientation represent, real measurement point by large stain represent, virtual P and Q measuring position represent by crunode by cross means and measuring position, is scaled virtual P and Q value at the measured current value in this position.

The target that is used for the equation (3) to (6) of optimizing process can utilize additional virtual information according to as additional in getting off:

Wherein:

J is according to the target of equation (3) to (6),

The J' extended target,

The quantity of the node region that NVNA is virtual,

By the voltage in virtual node region and the phase angle of WLS algorithm estimation, and

The voltage in virtual node region and phase angle according to the calculation of power flowmeter.Virtual node region must satisfy the first Kirchhoff's law:

$\underset{i=1}{\overset{\mathrm{NLDk}}{\mathrm{\&Sigma;}}}{P}_i^{\mathrm{Ek}}+\underset{i=1}{\overset{\mathrm{NBRk}}{\mathrm{\&Sigma;}}}{P}_i^{E,\mathrm{Brk}}=0$

$\underset{i=1}{\overset{\mathrm{NLDk}}{\mathrm{\&Sigma;}}}{Q}_i^{\mathrm{Ek}}+\underset{i=1}{\overset{\mathrm{NBRk}}{\mathrm{\&Sigma;}}}{Q}_i^{E,\mathrm{Brk}}=0$

Wherein:

The quantity of the load that NLDk is related with virtual node region k,

The quantity of the branch that NBRk is related with virtual node region k,

The load i of the estimation related with virtual node region k, and

The stream that flows through the branch i related with virtual node region k of estimating.

In addition, consider additional boundary condition in equation (4) and (5).Can consider virtual power measurement in the mode as real power measurement during estimating thus, only need consider a less weighting.Virtual power measurement can calculate to determine by the load flow that can carry out before estimating.

Fig. 6 shows the flow chart for the embodiment of estimation procedure.Begin this process in step 100.Form in step 101 and measure fragment.In step 102, current measurement value " from bottom to top " is scaled P and Q value.Estimate load in step 103.Carry out the calculating of power stream in step 104.Whether check in step 105, be the first iterative step.If so, go to step 106, otherwise go to step 107.

Whether check in step 106, be grid network or the network with parallel feed-in.If so, change to measure fragment and proceed step 102 in step 108.If not, go to step 107.

Carry out the inquiry of describing in step 107: check the wasted power P that determines in Fig. 6 in the iterative step of in succession following _LossDifference whether less than predetermined threshold epsilon _Loss, and the voltage V that determines in the iterative step of in succession following _maxDifference whether less than predetermined threshold epsilon _VIf two conditions all satisfy, finish the method (step 109).Otherwise returning step 102 by redirect continues to optimize.

Figure 7 illustrates the block diagram of device 200, utilize this device can produce the status signal of the state that shows energy transmission equipment.

Device 200 comprises memory SP, has stored load data Li(t=0 in this memory).Load data Li has described for i is individual and has loaded on active-power P and/or the reactive power Q that power grid operation business side reduces, and this i load is connected with energy transmission equipment.

Pretreatment unit STLS is connected with memory SP, and load data Li(t=0 can be read and process to this pretreatment unit from memory SP).As long as also there is not input value aspect estimation unit DSSE, pretreatment unit is just with load data Li(t=0) the means for correcting STLF that is sent in rear layout.On the contrary, if there is the load data LiDSSE that is estimated by estimation unit DSSE, pretreatment unit STLS can determine, whether it further transmits this load data LiDSSE or load data Li(t=0).For this reason, pretreatment unit STLS for example can check, whether surpasses predetermined threshold value with the predicting reliability of the formal definition of weighted value or weight coefficient wLiDSSE.If weight coefficient wLiDSSE surpasses threshold value, the means for correcting STLF that preferably the load data LiDSSE that estimates further is sent in rear layout of pretreatment unit STLS, otherwise transmit load data Li(t=0).The load data that is further transmitted by pretreatment unit STLS represents with Reference numeral LiSTLS in Fig. 7.

In addition, pretreatment unit STLS further transmits weighted value or weight coefficient wLiSTLS, the predicting reliability of the load data LiSTLS that its expression further transmits.

In the means for correcting STLF of rear layout inspection, forming further, whether the weather supposition on the basis of the load data LiSTLS of transmission is available.For this reason, it is with the weather value K(t of current measurement) (for example temperature value, humidity value and/or monsoon intensity value) with as the basis of the load data LiSTLS of further transmission and the weather value that consists of the load data LiSTLF that weather proofreaies and correct compare.Means for correcting STLF is for example according to following application correction function f:

LiSTLF=f(LiSTLS,T(t),T_STLS,W(t),W_STLS,H(t),H_STLS)

Wherein:

F weather correction function

The temperature of the current measurement of T (t)

T_STLS is as the temperature on the basis of load data LiSTLS

The humidity of the current measurement of H (t)

T_STLS is as the humidity on the basis of load data LiSTLS

The monsoon intensity of the current measurement of T (t), and

T_STLS is as the monsoon intensity on the basis of load data LiSTLS

Correction function f for example can be according to the product of following setting and weather-dependent correction coefficient fSTLS,

LiSTLF=LiSTLS*fSTLS(K(t))

In order to proofread and correct to avoid vibration by weather, weather proofreaies and correct that can also numerical value to be set level and smooth in addition, and method is about predetermined time interval average climate value before each Measuring Time point.

If the time point of proofreading and correct for weather does not provide current weather value, but for example only provides the weather value by a front iterative step, however this weather value still is used for proofreading and correct.Preferably, consider the timeliness separately of weather value by the time factor ZF of exponential damping, this time factor is in the situation that more old the converging to of weather value approaches zero.Time factor ZF for example can have following form:

ZF(t)=exp((t-t')/t_ref)，

Wherein t represents that current time point, t' represent to record the time point of weather value and t_ref and represent the attenuation constant of being scheduled to.

Correction function f for example can the following expression about such time factor

LiSTLF=LiSTLS*fSTLS(K(t))*ZF(t)

Load data LiSTLF after means for correcting STLF proofreaies and correct weather further is sent to after-treatment device PP, and energy consumption measurement device AMI is connected with this after-treatment device with AMR.Energy consumption measurement device AMI and AMR measure the consumption measured value E(t at predetermined network node place) and this its further be transported to after-treatment device PP.After-treatment device PP will consume measured value E(t) compare with load data LiSTLF after weather is proofreaied and correct, and if the load data LiSTLF after weather is proofreaied and correct with consume measured value E(t) different, carry out correction.For example after-treatment device PP is applied to load data LiSTLF and weight coefficient wLiSTLS after weather is proofreaied and correct with correction function q1 or q2, according to

LiPP=q1(LiSTLF,E(t))

wLIPP=q2(wLiSTLS,E(t))

Wherein

Q1 is used for the correction function of load data

Q2 is used for the correction function of weight coefficient

Load data after the correction of LiPP after-treatment device, and

Weighted value after the correction of wLIPP after-treatment device.

After weighted value wLIPP after having formed the load data LiPP after proofreading and correct and having proofreaied and correct, after-treatment device PP will have the load of the load data LiPP after correction and distribute to respectively the electric loading group, and the electric loading with similar predicting reliability is included in this load group.For this reason, after-treatment device PP for example can introduce the weighted value wLIPP after correction, and identical load group is distributed to respectively in all loads with similar weighted value wLIPP.

Usually, industrial load (such as factory etc.) has larger predicting reliability than private load (private home), thereby forms respectively at least one load group for industrial load with for private load.

Then, the load data LiPP after proofreading and correct is fed into estimation unit DSSE together with the weighted value wGruppe of " load data of prediction " and load group.

Estimation unit DSSE also processes the real electrical measured value of measuring, for example current value I of current measurement, magnitude of voltage U, active power value P and/or reactive power value Q except the weighted value wGruppe of load data LiPP and load group.

Under the condition that is introduced in the data that input side applies, estimation unit DSSE carries out the estimation of load and the estimation of power stream, having described in conjunction with Fig. 1 to Fig. 6 as this point.At this, it also considers the weighted value wGruppe of each load group especially except the load data LiPP of prediction.

Form the load data LiDSSE of new estimation and the weighted value wDSSE of new estimation in the scope of estimating, it is sent to pretreatment unit STLS, can begin new iterative step thus in the scope of iterative method.

Estimation unit DSSE is in the scope of estimating or produce independently status signal Sz, and this status signal shows at least one state of energy transmission equipment.Status signal is estimated as current value, magnitude of voltage or performance number, the measurement parameter of therefrom deriving, power stream and/or load that " state " for example may be displayed on in the network node of energy transmission equipment one.As status signal, also can produce the alarm signal of display alarm state, or show wrong rub-out signal.

For example can be by device VVC and the further treatment state signal of the SCADA Sz in rear layout.

In Fig. 7, pretreatment unit STLS, memory SP, means for correcting STLF and estimation unit DSSE consist of control device 210 jointly, it is applicable to: form load group, load is distributed to load group and distributed respectively independent weighted value to load group, this independent weighted value has been described the predicting reliability to the load data of the prediction of the load of load group distribution, and check the state of energy transmission equipment under the condition of introducing measured value, load data and weighted value, and produce the status signal of show state.

Interface 220 is used for the input electrical measured value, and this electrical measured value is measured about at least one electrical measurement parameter for the predetermined network node of energy transmission equipment.

Claims (9)

1. method for generation of status signal (Sz), this status signal has shown the state of energy transmission equipment, wherein

-measure about the electrical measured value of at least one electrical measurement parameter for the predetermined network node of energy transmission equipment and

-the status signal of generation show state under the condition of introducing described measured value,

It is characterized in that,

-give the electric loading the be connected to energy transmission equipment load data of the prediction of the electrical characteristics of distribution forecast load separately respectively,

-electric loading is distributed to respectively the electric loading group, the electric loading with similar predicting reliability is included in this load group,

-distribute independent weighted value for respectively each load group, this independent weighted value has been described the predicting reliability of load data of the prediction of the load of distributing to load group, and

-form status signal under the condition of introducing measured value, load data and weighted value.

2. method according to claim 1, is characterized in that,

-provide at least one that has respectively at least one energy consumption measurement device consume measured value electric loading load group and for the other load group that does not have the electric loading that consumes measured value, and

-in the situation that electric loading is assigned to load group, consider predicting reliability and the existence that consumes measured value.

3. method described according to any one in the claims, is characterized in that, measures at least one current weather measured value and proofread and correct weighted value and/or load data under the condition of the weather measured value of introducing described current measurement.

4. method according to claim 3, is characterized in that, if the weather measured value of current measurement is different from predetermined weather rated value, proofreaies and correct.

5. method described according to any one in the claims, is characterized in that,

-under the condition of the load data of introducing electrical measured value, prediction and weighted value, for the measured parameter value of the network node Calculation Simulation of energy transmission equipment,

-the state of inspection energy transmission equipment under the condition of the measured parameter value of introducing described emulation.

6. method according to claim 5, is characterized in that, for the measured parameter value of the network node Calculation Simulation that does not have electrical measured value.

7. method described according to any one in the claims, is characterized in that,

-for the measured parameter value of the predetermined network node Calculation Simulation that has electrical measured value,

-measured parameter value of described emulation is compared with the measured value of measurement, and

-load data that form to optimize, method are to change the load data of prediction until minimum or reach or lower than predetermined threshold value in the measured parameter value of emulation and the deviation between electrical measured value.

8. method according to claim 7, it is characterized in that, in the situation that change the weighted value that load data considers to distribute to each load group, method is that its weighted value has been shown that the load data of less predicting reliability has shown that than its weighted value the load data of larger predicting reliability changes in the larger context.

9. the device for generation of status signal (Sz) (200), this status signal has shown the state of energy transmission equipment, this device has

-being used for the interface of input electrical measured value, this electrical measured value is measured about at least one electrical measurement parameter for the predetermined network node of energy transmission equipment,

-control device, it is applicable to: form load group, load is distributed to load group and distributed respectively independent weighted value to load group, this independent weighted value has been described the predicting reliability to the load data of the prediction of the load of load group distribution, and check the state of energy transmission equipment under the condition of introducing measured value, load data and weighted value, and produce the status signal of show state.

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